Detection and Rectification of Distorted Fingerprints

Detection and Rectification of Distorted Fingerprints

Abstract— Elastic distortion of fingerprints is one of the major causes for false non-match. While this problem affects all fingerprint recognition applications, it is especially dangerous in negative recognition applications, such as watch list and deduplication applications. In such applications, malicious users may purposely distort their fingerprints to evade identification.In this paper, we proposed novel algorithms to detect and rectify skin distortion based on a single fingerprint image. Distortion detection is viewed as a two-class classification problem, for which the registered ridge orientation map and period map of a fingerprint are used as the feature vector and a SVM classifier is trained to perform the classification task. Distortion rectification < Final Year Projects 2016 > or equivalently distortion field estimation is viewed as a regression problem, where the input is a distorted fingerprint and the output is the distortion field.